|
|
Absolute deviation, 绝对离差
8 n8 G: G1 H2 QAbsolute number, 绝对数9 P$ m. H3 \: d; f" t( w
Absolute residuals, 绝对残差+ Z+ i, u" E, F. n, T
Acceleration array, 加速度立体阵
' y1 B$ F. t$ f; J1 | dAcceleration in an arbitrary direction, 任意方向上的加速度6 C+ F8 {1 L+ n; ?1 v1 s- C
Acceleration normal, 法向加速度
" i% D+ Y8 }( I. JAcceleration space dimension, 加速度空间的维数
8 r, a' R" @' SAcceleration tangential, 切向加速度 s- b, Q5 a+ k! b
Acceleration vector, 加速度向量7 U6 V9 R9 P* c" f, K2 Q
Acceptable hypothesis, 可接受假设. b: ~; B+ u) y0 q0 [) r: R: D
Accumulation, 累积4 n+ s9 Q) E# w% g% ^
Accuracy, 准确度
3 ?- o6 Z8 p4 c0 a8 gActual frequency, 实际频数. F4 @2 |* |7 F
Adaptive estimator, 自适应估计量
8 h/ u1 Q% A$ h9 v0 P _7 DAddition, 相加
7 x ~# g0 r) u$ o$ bAddition theorem, 加法定理
. I" {. `# S" [ E: r6 I, y rAdditivity, 可加性
3 F* j0 _/ ~5 k( D1 z+ j3 hAdjusted rate, 调整率
( I) O! c& P+ Q3 @0 hAdjusted value, 校正值
' ^5 C& \! _4 bAdmissible error, 容许误差$ v* r1 v$ z: F2 v$ ? O2 }, k3 h
Aggregation, 聚集性
, s" Q7 P. _5 Y) z& V$ e6 sAlternative hypothesis, 备择假设
b7 j+ ]. q" yAmong groups, 组间
+ Z9 U2 ]9 h0 L' w9 M& y8 xAmounts, 总量9 E- F, B+ `# X
Analysis of correlation, 相关分析
' D; V( X7 A5 fAnalysis of covariance, 协方差分析
6 v7 R& ~- P P) Z& g, n. [Analysis of regression, 回归分析
( W1 K* g1 }6 oAnalysis of time series, 时间序列分析
" T9 N; C' _/ L# } D4 PAnalysis of variance, 方差分析
- c$ r3 T$ Z5 J C4 V3 VAngular transformation, 角转换( I5 f: e1 F# V+ @: H2 [: F
ANOVA （analysis of variance）, 方差分析
( `. p8 d6 C! j3 U9 u3 dANOVA Models, 方差分析模型/ @5 o# r+ Y! G' D8 ^0 k; b
Arcing, 弧/弧旋& u/ Q+ I4 r) A9 F+ p0 p1 y0 t
Arcsine transformation, 反正弦变换
# y7 p, C; W0 _' y3 NArea under the curve, 曲线面积
2 _, Y s$ H3 Z; E0 h8 GAREG , 评估从一个时间点到下一个时间点回归相关时的误差
/ Z- f; U( D; d' l( zARIMA, 季节和非季节性单变量模型的极大似然估计 : \) Y7 I, @$ \. W1 G' f
Arithmetic grid paper, 算术格纸
7 t; A; L/ C) |8 q V9 c {# PArithmetic mean, 算术平均数
8 Y1 ^! i, Y+ }! t0 rArrhenius relation, 艾恩尼斯关系
( Q6 O" H1 s o" K+ q, zAssessing fit, 拟合的评估" d' `8 H: q4 K! M0 |) Z: v
Associative laws, 结合律/ p% P( j: q( S; d5 \& a+ n
Asymmetric distribution, 非对称分布/ _! M. a! w" u9 G+ f" m
Asymptotic bias, 渐近偏倚
7 |. B& x L9 m* lAsymptotic efficiency, 渐近效率
+ w7 {4 S7 O' gAsymptotic variance, 渐近方差
0 }5 w) t( t, i, Q( V/ [; B5 TAttributable risk, 归因危险度
4 I; d+ y( X) z+ PAttribute data, 属性资料
% ^2 j( N7 A. } p# Q# Q5 ?Attribution, 属性
# Z- Y V1 k8 j& v) J; MAutocorrelation, 自相关
" z3 ~% g5 @- _, y) V) v0 b; a4 dAutocorrelation of residuals, 残差的自相关! X3 D3 B& r# \; d
Average, 平均数& ?( K2 D ~' V3 f2 P) j ]
Average confidence interval length, 平均置信区间长度
: c& U7 m: @2 zAverage growth rate, 平均增长率
4 {1 U: v' I1 g) P0 JBar chart, 条形图
, E# t/ \7 \6 c# u: P8 TBar graph, 条形图
+ V- t5 U. K# M# f$ c. aBase period, 基期. d% q" g# i% A
Bayes' theorem , Bayes定理& N3 { p7 D* F) L. F' q# p) ?5 t
Bell-shaped curve, 钟形曲线
' A9 l5 y5 r0 u# z! wBernoulli distribution, 伯努力分布
- D6 W' g3 O0 n+ @& |$ A: A3 aBest-trim estimator, 最好切尾估计量
5 s- R" w2 V ]' L; D: @# ` U7 t LBias, 偏性$ H7 J( {8 L/ M/ Y$ C
Binary logistic regression, 二元逻辑斯蒂回归
4 `3 _, ^: x7 Y" MBinomial distribution, 二项分布6 e0 h, E' y% t' ~& A9 t
Bisquare, 双平方% x9 b- D6 G6 [
Bivariate Correlate, 二变量相关* i5 g6 q, k s' V, l1 G
Bivariate normal distribution, 双变量正态分布
4 L( w0 ^ ] o4 r% N IBivariate normal population, 双变量正态总体
: @3 e, O/ H0 K, ]' x, y: yBiweight interval, 双权区间
: \' g. m& y/ S$ C: k/ CBiweight M-estimator, 双权M估计量# Z( e, ?5 b) D
Block, 区组/配伍组
t7 A/ a6 t, r4 t5 h: GBMDP(Biomedical computer programs), BMDP统计软件包8 p f- q* T ]" w% l
Boxplots, 箱线图/箱尾图
+ k8 [) [6 M! Y( F. F6 }5 r: E1 VBreakdown bound, 崩溃界/崩溃点* q: Z! Q% ]) ^
Canonical correlation, 典型相关
% {) h! D5 X9 Q1 y. g7 g3 `Caption, 纵标目, N; S7 d8 Y( ]# k( L g
Case-control study, 病例对照研究% r2 u! | X) ~3 s
Categorical variable, 分类变量. }. J" h0 q' U
Catenary, 悬链线
L! U" G1 j$ J" \! e3 h4 WCauchy distribution, 柯西分布+ _. j5 F2 m6 s# f) ^2 H
Cause-and-effect relationship, 因果关系
3 I2 A& ^6 L. `3 q$ A4 h4 |; SCell, 单元# i! }! W; m8 ?4 I7 z0 t- J- b
Censoring, 终检) i( o3 B$ g( W3 O; s$ A
Center of symmetry, 对称中心
$ C, @) a' @; O; ~; t* \Centering and scaling, 中心化和定标. M: r Y% M- N3 V7 a T
Central tendency, 集中趋势0 }3 H s- q1 y$ b2 B, b# I0 ?0 }8 \5 P7 |
Central value, 中心值: ]% f8 k6 R$ L- G/ \* t6 w+ E
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
, ?5 j/ j0 w9 M' n' jChance, 机遇
# w2 ?3 l' V* o, H. vChance error, 随机误差
* F/ I% {9 q7 s+ g9 m; f9 P6 |4 b9 HChance variable, 随机变量# [$ i5 d" k% h$ t& u" G. y2 B A/ g
Characteristic equation, 特征方程
' T1 j) I: _' y5 P. U$ lCharacteristic root, 特征根2 }/ D7 I' K: Z( f/ S
Characteristic vector, 特征向量
8 O, [: M' N2 j0 }. Y, P7 W" e* CChebshev criterion of fit, 拟合的切比雪夫准则
) \# H$ } h& ?Chernoff faces, 切尔诺夫脸谱图
* W; I/ z& e8 j0 f8 }Chi-square test, 卡方检验/χ2检验
+ }+ t1 i7 v v% A. K5 U8 K/ yCholeskey decomposition, 乔洛斯基分解7 {: l, G1 s$ Q
Circle chart, 圆图
: x$ v* i" S1 q- wClass interval, 组距7 L. N' ?$ R; A4 I7 J! o j
Class mid-value, 组中值
5 l C! w5 A& B9 {8 yClass upper limit, 组上限$ ?; x C( z$ d
Classified variable, 分类变量8 X' t! x& ^& u; z; u4 `/ v
Cluster analysis, 聚类分析
4 U0 `7 @% Q( I1 p5 NCluster sampling, 整群抽样
, s$ M! I' v2 k2 G. rCode, 代码# |/ b' a9 J0 E4 v! E9 f$ c
Coded data, 编码数据
+ u. o# P: f5 T! f1 Q" i/ ECoding, 编码$ x7 l/ W. F+ J5 `; Z2 j$ w A
Coefficient of contingency, 列联系数- o, k) v3 v0 U' X: N6 X% Q
Coefficient of determination, 决定系数( ~ ]3 l% z: F/ L
Coefficient of multiple correlation, 多重相关系数
& W6 c: k8 }+ _0 T. oCoefficient of partial correlation, 偏相关系数
/ {3 q2 X a3 `Coefficient of production-moment correlation, 积差相关系数) o* V( t" q' R9 i
Coefficient of rank correlation, 等级相关系数4 U( n/ [% k: x% L% i% E
Coefficient of regression, 回归系数
" b1 K* p" l5 Y$ |& q$ i3 j6 VCoefficient of skewness, 偏度系数0 {& I) V, @* p5 W6 M
Coefficient of variation, 变异系数
# {; b! i' @- N8 u$ OCohort study, 队列研究 `0 d, K8 U u( r) j2 `1 ^
Column, 列5 J, p; u3 d! @ S$ @' s
Column effect, 列效应& E2 F( y& t; k1 j' [: V/ P3 i
Column factor, 列因素
?( o0 T8 o1 m# i' z: _+ {: ACombination pool, 合并& ~* f& V ]- s
Combinative table, 组合表' W) q, }) l$ @: E0 l
Common factor, 共性因子( J- ^; s( ]3 F* O) T% ?
Common regression coefficient, 公共回归系数( D6 ?, q" s% ?" s
Common value, 共同值- d% A: {+ Q5 X* j$ h- b1 r
Common variance, 公共方差
, Y$ M! @# v: l& q; hCommon variation, 公共变异
) f4 u$ {1 V' z+ u% V, ^- Z! ACommunality variance, 共性方差8 e, X# I/ D) Y5 p9 ^. A* _, ^
Comparability, 可比性9 \* N( u. A8 K' c r& _) O
Comparison of bathes, 批比较
& B) H' A1 Q5 z3 S( ]6 VComparison value, 比较值
* G) f/ a* j7 o* nCompartment model, 分部模型
- w+ t6 Q$ A2 Z5 c5 dCompassion, 伸缩
- C& K! N+ f0 U3 T$ xComplement of an event, 补事件4 Z4 z. d4 Y. }6 Q
Complete association, 完全正相关
% ^" o% I; e, u, B' e) M( wComplete dissociation, 完全不相关* P7 N7 ^7 T% J {0 u. ?. X) L, D8 h
Complete statistics, 完备统计量3 N! _7 n7 I) b
Completely randomized design, 完全随机化设计
8 s5 R8 p- A5 O' ^Composite event, 联合事件
8 Z/ z8 F0 `( R; }4 c7 sComposite events, 复合事件8 U. I* e+ R; I9 O6 W8 g1 H! D% G
Concavity, 凹性# X3 }6 R: N& e; \% b
Conditional expectation, 条件期望, X2 L9 ~3 `% d+ i
Conditional likelihood, 条件似然4 P, W! X4 _ L" k9 x+ l/ X
Conditional probability, 条件概率3 l2 d3 K# i* N: Z. @ b3 e/ C
Conditionally linear, 依条件线性) u- f. k: e7 K I) Q! Y1 @
Confidence interval, 置信区间5 y4 W2 `9 c* m1 Y1 Q# x% x
Confidence limit, 置信限
$ Z- w4 I5 A& w& _9 d- g3 Z& bConfidence lower limit, 置信下限3 @1 ~: Q J% w0 x6 A, R( R8 p
Confidence upper limit, 置信上限
1 M+ S! K. l4 O* i% N% \& {Confirmatory Factor Analysis , 验证性因子分析
; F4 @* x; R, ]9 v0 LConfirmatory research, 证实性实验研究 H: T. Q* s0 a6 ?
Confounding factor, 混杂因素
- ^1 V& e! r# \ B* v& MConjoint, 联合分析$ y- N- t" E6 V
Consistency, 相合性
" U6 c2 w+ \4 k' G% OConsistency check, 一致性检验
* N7 P- S4 ~4 \$ u+ ?Consistent asymptotically normal estimate, 相合渐近正态估计
3 l- [: O) u/ Y5 L. N7 q7 i+ x* N# oConsistent estimate, 相合估计
% R9 w" m$ x! u" oConstrained nonlinear regression, 受约束非线性回归
" ~* a* V5 z( V0 V4 f WConstraint, 约束
& D/ V; ^9 k. @8 k b) {Contaminated distribution, 污染分布! U2 p1 A- N8 J' G5 @
Contaminated Gausssian, 污染高斯分布( A5 {7 \; l/ S( O8 `; |, c
Contaminated normal distribution, 污染正态分布
( }& y. Y% @) T. ^Contamination, 污染
4 M( }8 K# m9 r/ ^Contamination model, 污染模型1 M! ~- l; \: i0 F5 h W9 \
Contingency table, 列联表2 o, W. H5 [' P
Contour, 边界线) P" V) n( l8 T4 s
Contribution rate, 贡献率
$ D$ N: L* z3 U9 qControl, 对照9 ?: L; K# Z$ s; u1 K/ `# n
Controlled experiments, 对照实验
& m; a2 Q. q# p4 H8 R6 V: UConventional depth, 常规深度
* K( j$ g( ~7 \* I1 S0 {' h3 Z# M9 v# ]Convolution, 卷积% @9 Z7 ~; `7 o
Corrected factor, 校正因子
9 K# X! q1 g4 K" }% y8 n! vCorrected mean, 校正均值
. D! Q! {% m) i# FCorrection coefficient, 校正系数; l( A6 l8 L# O& ~2 C* @
Correctness, 正确性
' g: C2 w4 \( X8 ~0 `% ZCorrelation coefficient, 相关系数
$ @$ X8 ?8 ] {5 aCorrelation index, 相关指数
6 M% @9 z& G) p! ]4 sCorrespondence, 对应. R/ U& r" N- d1 U4 u2 A
Counting, 计数: y( Y* n# ^) j
Counts, 计数/频数2 |5 ?0 V4 i' K: U7 G5 ?) h4 t
Covariance, 协方差
! r8 e5 ] h9 v' A7 C" h+ bCovariant, 共变 3 @) T% d3 } a; W9 T' j
Cox Regression, Cox回归
. t- H$ O9 F: aCriteria for fitting, 拟合准则
8 z- _0 o8 z6 f4 g# O$ n# S. u/ FCriteria of least squares, 最小二乘准则
a0 [# T% J9 Z3 ]+ U# Q1 rCritical ratio, 临界比- R; K6 m$ J) l3 X- @1 g- T
Critical region, 拒绝域/ d8 k0 ^! e) B( Q! Z2 I
Critical value, 临界值
: ~; {" y9 n. f! iCross-over design, 交叉设计
0 r. d, ]% X) s( \( A7 ECross-section analysis, 横断面分析$ [$ {- w k( ]7 C8 p0 Q+ S
Cross-section survey, 横断面调查- O1 ^# f" t& g- E0 x
Crosstabs , 交叉表
$ s* `/ J# \5 t! V8 ICross-tabulation table, 复合表
4 v. g7 V* s! O2 X0 {% \Cube root, 立方根
; |! } Y( u( f% Z' d5 T- ?Cumulative distribution function, 分布函数3 c- t4 i5 _1 X- w5 Z, f
Cumulative probability, 累计概率
+ b2 R4 E' K1 {Curvature, 曲率/弯曲
1 v6 b+ v' m* g' ?# bCurvature, 曲率! E0 p4 U5 p& N- S; l! i
Curve fit , 曲线拟和 9 k% e; |1 `' B7 x3 x; k
Curve fitting, 曲线拟合+ Q8 X' V% b6 H, h# _6 _! W
Curvilinear regression, 曲线回归" c/ M, S5 H$ F! s( Q
Curvilinear relation, 曲线关系
6 V! }7 E" r; g1 }( m/ t: t( T/ ]. QCut-and-try method, 尝试法
" I- U( X$ Q. dCycle, 周期
- W& Y' E/ ?, W5 N& p: ^0 NCyclist, 周期性* |/ q& F e( y3 p
D test, D检验
( k6 W% ^- O! y. B; f3 EData acquisition, 资料收集
: S' D5 A3 d5 E" x4 C" WData bank, 数据库
- r2 {; z e7 p) G/ hData capacity, 数据容量
+ d$ w+ x* s ^# @Data deficiencies, 数据缺乏
7 |) Z9 _# `7 N! l! jData handling, 数据处理
4 x8 q8 }$ m( }* m! z+ KData manipulation, 数据处理
: Y1 r8 g7 D; ]2 hData processing, 数据处理
& e* [! o; V' WData reduction, 数据缩减
[; [* Q! a6 x& O- ]$ m7 TData set, 数据集; `( N+ [$ Q5 W
Data sources, 数据来源
e( V, N1 C! w+ R: p5 AData transformation, 数据变换
2 K* b& S7 f' Z" H$ M3 ?Data validity, 数据有效性# L9 N* p# B9 g' D$ s2 e, |
Data-in, 数据输入
; n1 n9 D5 _6 eData-out, 数据输出
5 [7 t' E+ t V$ x# f( HDead time, 停滞期
; P# A5 S1 F! V) iDegree of freedom, 自由度; M c2 K; M* }" Q7 j
Degree of precision, 精密度) f9 s# C! G7 T ~
Degree of reliability, 可靠性程度" U0 `( B5 v) z9 x d
Degression, 递减4 a# d2 X3 O' ~! H& e9 I2 A
Density function, 密度函数1 _( K: h3 _: [
Density of data points, 数据点的密度0 \' q, Z9 v, ? r1 G. E1 O: Z
Dependent variable, 应变量/依变量/因变量; k n- `& `2 n5 z, O
Dependent variable, 因变量
+ k: D I V ~2 `! h) x( v& \. F# hDepth, 深度$ Q; V1 `& S+ C' E& w% u+ T7 k
Derivative matrix, 导数矩阵
+ q: H; C/ B. ?: u. {8 ^Derivative-free methods, 无导数方法& @# `. x9 O9 A* |6 i. z
Design, 设计
* V: `7 N. \/ X7 j: h8 NDeterminacy, 确定性
: m% |# \4 ^+ g* fDeterminant, 行列式: _8 j, G* d- H
Determinant, 决定因素
8 S& N# S, E5 h' Z/ L& U) f' NDeviation, 离差 T+ k8 R* C9 g: A1 V7 j2 Z0 |3 `
Deviation from average, 离均差 w( t \& S! L$ f1 _' x
Diagnostic plot, 诊断图" Y3 D% _, q7 A! k# m- t) e W+ n
Dichotomous variable, 二分变量
/ w* `* G3 r. ^" Y k* _6 g* bDifferential equation, 微分方程! H, V4 y& B% n- A, w8 h
Direct standardization, 直接标准化法/ ^; U/ Y8 v- ?4 N, H
Discrete variable, 离散型变量
* A5 i2 w! n" q- lDISCRIMINANT, 判断
. S9 w, E, h! d8 E" z+ k9 k: t4 t2 sDiscriminant analysis, 判别分析
6 _* h0 w5 @- w) QDiscriminant coefficient, 判别系数$ k3 Y# y! h0 A
Discriminant function, 判别值
5 b4 Y8 T6 C$ P' E; wDispersion, 散布/分散度$ I+ G4 @; _6 o! p N8 R1 J
Disproportional, 不成比例的6 z# P8 b; a! t
Disproportionate sub-class numbers, 不成比例次级组含量
1 l+ R7 f# e' L& m5 N3 b. d8 \Distribution free, 分布无关性/免分布+ G& n) N- i) N1 x; ]
Distribution shape, 分布形状( D* v0 B1 U' Z, b0 k( x# X% F
Distribution-free method, 任意分布法
. J9 m6 N! |# Y' C( a' q3 dDistributive laws, 分配律
) n" I1 C* G, ^# D) M T( D% K' vDisturbance, 随机扰动项
7 F9 u) t8 d3 S0 o7 a, F* d6 TDose response curve, 剂量反应曲线
. n, Y, \& r8 i7 \ w) CDouble blind method, 双盲法- r5 t6 [( v7 K. J9 G2 z1 f
Double blind trial, 双盲试验; F4 t( P+ m0 A
Double exponential distribution, 双指数分布* \4 d5 V7 F' W; _% i
Double logarithmic, 双对数7 M- S2 M: K3 m) p, v9 ^5 @
Downward rank, 降秩6 E2 s! H' M& m2 ~2 k9 ^6 b
Dual-space plot, 对偶空间图
7 H+ ?/ }5 ~9 G% WDUD, 无导数方法
# X5 W% R: m' b( zDuncan's new multiple range method, 新复极差法/Duncan新法
* J; ~3 A! e* q1 {. kEffect, 实验效应
1 K7 L' _+ H0 U) D2 L1 oEigenvalue, 特征值! f. |4 C* y6 v8 ^7 ]- G+ H0 {
Eigenvector, 特征向量) J' w; g1 E5 j, l9 }/ i
Ellipse, 椭圆
! d3 w# g4 K3 m/ uEmpirical distribution, 经验分布# ]7 C, Q, U) b; F' o
Empirical probability, 经验概率单位
4 [& s+ K9 i& L$ w" `1 JEnumeration data, 计数资料
' \) r9 h, G; i' \9 f# @- kEqual sun-class number, 相等次级组含量
2 L' X( _: s# w6 {; l$ jEqually likely, 等可能
3 N- |" M( R( d# _. U& B8 IEquivariance, 同变性
0 V9 r& D/ O z2 q; d( N2 P+ bError, 误差/错误
9 O, @% x( P! A4 r1 Y" HError of estimate, 估计误差
G- Y2 [, [. r2 xError type I, 第一类错误. ` v* |0 W! Q3 v
Error type II, 第二类错误7 x8 w x- U! f
Estimand, 被估量
$ G: {9 D1 [8 v6 j7 F; M; xEstimated error mean squares, 估计误差均方
& Z( M g S: \- mEstimated error sum of squares, 估计误差平方和# y& C% I. F+ l g9 K
Euclidean distance, 欧式距离/ r+ }! E3 _5 l7 J# I& \. _
Event, 事件+ j! q' e8 Y) b8 j8 p
Event, 事件
- X) p9 o& W# F8 H2 t) B8 HExceptional data point, 异常数据点
: b3 U- y+ [9 ?+ g6 V. a3 oExpectation plane, 期望平面, w) x# m# v/ }7 t
Expectation surface, 期望曲面# N9 s" [% U) r i- ^$ R( L
Expected values, 期望值% x9 d/ G K% H6 D
Experiment, 实验
: }" [4 x( r; s! m9 J2 QExperimental sampling, 试验抽样
5 C9 C) Y# @1 z8 t1 Y# L0 B' lExperimental unit, 试验单位
% L" m9 V/ c1 s! G8 [/ K* y* v) DExplanatory variable, 说明变量5 _' g: n) j2 T% g# K$ s8 w
Exploratory data analysis, 探索性数据分析; P3 c! J: A- J0 f; z! c
Explore Summarize, 探索-摘要/ Y* s% n4 N8 |/ T% `* I$ F- ^' w* V
Exponential curve, 指数曲线
, ~4 s% ~, b. L1 DExponential growth, 指数式增长
: R, y5 B. _! Z$ t9 s/ W! D" gEXSMOOTH, 指数平滑方法
) i! W* X" p, vExtended fit, 扩充拟合# a& l A9 x- l* J
Extra parameter, 附加参数# y) M9 G! L8 e* g0 Z3 Y3 L6 t6 f
Extrapolation, 外推法
% g0 G! c i6 J3 _Extreme observation, 末端观测值
# ?9 s5 r7 Z9 K) LExtremes, 极端值/极值
1 m$ J7 z) V$ v2 f ^F distribution, F分布
# G" E% N3 [8 OF test, F检验- s) m9 l p0 u% l; O- D9 H
Factor, 因素/因子
4 Q9 w5 ]+ E8 D: S6 _9 yFactor analysis, 因子分析5 t( \$ Q% _0 w$ p
Factor Analysis, 因子分析
, m, Q& N. { PFactor score, 因子得分 2 Z% Q5 P. \2 K8 Z: O' @1 g
Factorial, 阶乘' u7 _; S I& W9 _
Factorial design, 析因试验设计3 G6 \) M5 g9 p" y* Y
False negative, 假阴性
* {- p; r6 k2 r9 \3 MFalse negative error, 假阴性错误
4 t: S8 P4 R" v, l1 qFamily of distributions, 分布族
7 x( ^( k a7 xFamily of estimators, 估计量族1 ^$ _+ D' `7 q7 |6 r% G
Fanning, 扇面: F3 l! [; z# ?- X9 K O
Fatality rate, 病死率% r+ I$ E( R% W: k' @" a4 t. z* B
Field investigation, 现场调查* n# n4 o" Q3 |+ T. s9 h: I6 F6 s
Field survey, 现场调查
: d' b7 @- a; r' e' H4 C6 T4 H& HFinite population, 有限总体
1 ?+ f9 _5 t0 Q. k1 J% z+ xFinite-sample, 有限样本/ E3 x2 O( p, t/ s3 f. `0 r( }* v
First derivative, 一阶导数% t9 [1 y5 N' S4 d. t8 c. {
First principal component, 第一主成分 ~) d* A4 S+ q% d/ T" X; j
First quartile, 第一四分位数7 @+ R5 M: g; @6 ]8 f
Fisher information, 费雪信息量
$ r. Q+ y3 ?+ l7 A% b4 q; c: e# fFitted value, 拟合值
9 i3 Z% o4 m V: }6 v" g; CFitting a curve, 曲线拟合
1 _" J- b2 t" q4 m# MFixed base, 定基% b$ @( Q [* I' Q$ g0 G h
Fluctuation, 随机起伏* C l( p8 K( J& E+ i9 T
Forecast, 预测) Y5 n* q$ Y g- K1 Z9 g! V
Four fold table, 四格表
* X! R0 B) U* f, N. J2 C5 s) c% lFourth, 四分点9 T5 H- {7 R6 X& ]% R8 i) M
Fraction blow, 左侧比率* u% C) e+ `; s5 ^
Fractional error, 相对误差+ _/ ]7 v2 Z- Y9 S" I5 L4 U
Frequency, 频率
1 T& D2 r' d" l5 ~3 h% y# M! rFrequency polygon, 频数多边图8 s9 V* b0 G ~ O) a
Frontier point, 界限点
4 \, v0 r% T( y7 U1 V' hFunction relationship, 泛函关系
" k! @7 U7 m( F: p8 pGamma distribution, 伽玛分布% p8 G% W; ~" u$ v$ y$ t$ r
Gauss increment, 高斯增量
2 @0 z0 K" i. S5 a& D0 bGaussian distribution, 高斯分布/正态分布' Q7 u3 i, ?8 ]' _& R4 N# ~& o1 ~4 b
Gauss-Newton increment, 高斯-牛顿增量
% Z) |% _1 e8 U9 V0 AGeneral census, 全面普查
& @6 L+ C, U# v( h; tGENLOG (Generalized liner models), 广义线性模型
6 G8 g& X0 J' GGeometric mean, 几何平均数) L l2 ^ E$ m
Gini's mean difference, 基尼均差5 ~0 z2 g0 I% ^! }/ W( Q
GLM (General liner models), 一般线性模型
' m' R- q0 i5 D) L; k+ @Goodness of fit, 拟和优度/配合度3 q: B* k, j9 p( n: ]
Gradient of determinant, 行列式的梯度7 L j# x# j0 s8 s$ M
Graeco-Latin square, 希腊拉丁方3 b" {. U" w* ]/ H: d9 A$ `1 H
Grand mean, 总均值
/ w: N+ z" m% R" ]# x' Y8 FGross errors, 重大错误
: N- \$ {0 Y- B1 e( h4 h! zGross-error sensitivity, 大错敏感度
2 Z$ u1 q; N6 R$ R7 I/ OGroup averages, 分组平均
r$ \: I& h; `Grouped data, 分组资料. }& x/ ]% C0 c# j; U3 Z: a/ T
Guessed mean, 假定平均数
d" Z# }2 t9 Z2 r5 oHalf-life, 半衰期. u# v7 o0 D! `7 Y" i }$ e x
Hampel M-estimators, 汉佩尔M估计量; W* g' E9 ^4 M
Happenstance, 偶然事件
! P! K1 @ ?# Y- ?/ X% C( _" nHarmonic mean, 调和均数% d( i; p. J/ u' d5 k, h/ \- T
Hazard function, 风险均数9 v' b. ]9 \! H7 w
Hazard rate, 风险率, z6 e' w/ a n: k7 |5 s
Heading, 标目 ( F" d7 n, t- I& Q" A0 l% f
Heavy-tailed distribution, 重尾分布
G2 u, Z4 w' ^( w# b QHessian array, 海森立体阵) e9 x$ Z. d2 U
Heterogeneity, 不同质8 W. a0 z5 S2 Q; u3 e5 }
Heterogeneity of variance, 方差不齐
+ N' U3 |* v0 t! eHierarchical classification, 组内分组9 {1 {6 M& J9 K$ L i! @# ]
Hierarchical clustering method, 系统聚类法
. Y. u1 Z2 r. o+ H% cHigh-leverage point, 高杠杆率点7 G& C# Z6 v# J3 m: k' s1 V. f
HILOGLINEAR, 多维列联表的层次对数线性模型
7 T3 N% D! z% {. F _% G4 BHinge, 折叶点
5 j, K* k3 K. x6 O7 l. HHistogram, 直方图6 d+ Y1 b- `0 u! m- c9 S" C& J
Historical cohort study, 历史性队列研究 ; \5 _" T: y1 L) J: ], ?9 R; m
Holes, 空洞
r& O1 v# H$ ~& {! bHOMALS, 多重响应分析" z( U1 f+ I- A7 `: a0 R+ C
Homogeneity of variance, 方差齐性7 {; S9 i/ o% O+ _- R& i
Homogeneity test, 齐性检验8 \) h( D G/ b
Huber M-estimators, 休伯M估计量* }" x; S2 ]2 m, u* e
Hyperbola, 双曲线8 L* y$ i, T/ A! M2 T+ M& S
Hypothesis testing, 假设检验/ |" V5 }' q' Z% t8 N9 n- ]
Hypothetical universe, 假设总体3 P* U% Q7 b* S0 [% D6 ]) ]/ Y
Impossible event, 不可能事件( e/ ~, [ a( ] f
Independence, 独立性7 p( C( H, N6 Q; I# w& }% A
Independent variable, 自变量
( R" ]6 p5 `0 E) y: X' ^# gIndex, 指标/指数) t) ?& K" Y6 l+ [1 S! o8 F
Indirect standardization, 间接标准化法& Y1 h" R, b* O) l4 N
Individual, 个体
5 d; o5 j3 X& Z* @Inference band, 推断带
- P' A8 E# O8 t5 {* S; K" e9 I, pInfinite population, 无限总体
2 u d7 v, v7 g3 o! k$ TInfinitely great, 无穷大; l' s( ~# W) S& u2 x/ I
Infinitely small, 无穷小" G9 h: {; f, `; @4 E+ G& L
Influence curve, 影响曲线; D4 a" ]$ @+ Q0 o
Information capacity, 信息容量4 d2 \' ?+ z. I. B4 t$ N, Z& n9 ~
Initial condition, 初始条件2 ]% I7 s8 C7 {5 [; {9 G/ k
Initial estimate, 初始估计值8 F: i k1 K' c7 Z R$ J
Initial level, 最初水平
! ]/ I" \3 x4 O0 {, r! V0 d& KInteraction, 交互作用; A" X' y2 P; P& U
Interaction terms, 交互作用项
5 |- v" ^+ \" \Intercept, 截距
. E. Z, N# Y FInterpolation, 内插法3 s! { j4 p' q Y( H2 q1 q6 U
Interquartile range, 四分位距
: l4 v6 B2 V) g- o# ]: E+ H5 GInterval estimation, 区间估计
5 l* [, N0 r9 R/ W; Q" p* N" qIntervals of equal probability, 等概率区间
" A$ o0 o& V( k0 WIntrinsic curvature, 固有曲率4 |- J! f, x: l- Y1 f7 h
Invariance, 不变性
( t5 E8 y5 s' b% J3 T3 c( IInverse matrix, 逆矩阵
u; S8 @' h" L; _, {Inverse probability, 逆概率4 i! h# I* @8 a. |0 g( i g# h' }1 D
Inverse sine transformation, 反正弦变换7 O' H3 a) a0 j' `
Iteration, 迭代
( Z- `* n0 S! u! q/ @: IJacobian determinant, 雅可比行列式6 p/ ?4 a# I7 f! V& E* x
Joint distribution function, 分布函数- q# `7 A; O; T, B0 S9 ]
Joint probability, 联合概率" ^: K& _3 P5 v3 p5 c: v' u8 J( I* `
Joint probability distribution, 联合概率分布
' J* Y' R* {/ K3 w! [1 }/ ZK means method, 逐步聚类法- ^3 A, J3 v7 G# n6 ` W& |
Kaplan-Meier, 评估事件的时间长度
8 S6 N ]4 A6 Y5 B5 hKaplan-Merier chart, Kaplan-Merier图1 A6 \) ^+ R. B. ?3 _+ u# C
Kendall's rank correlation, Kendall等级相关
7 F! S( L5 ?# g2 V BKinetic, 动力学$ N- j( L) w" g5 N1 d
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验1 i$ a( ?. W# V" Q. U K
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验. O' b" L* Y: s) P
Kurtosis, 峰度
# q8 R, ^# r D( }: t6 W' SLack of fit, 失拟
/ ?' h, r5 Q/ Z% z' ]- w5 a6 l0 LLadder of powers, 幂阶梯
9 c1 U8 L0 S! d* m2 \ QLag, 滞后
7 b$ N$ P2 [' g% e2 `1 N% k/ CLarge sample, 大样本, S5 Y7 L2 N0 [2 {& g
Large sample test, 大样本检验7 m3 }6 s! K3 j
Latin square, 拉丁方
2 f$ J. ?& j! [5 e! {Latin square design, 拉丁方设计
: z- g4 X7 B3 ZLeakage, 泄漏7 g5 _( o, _9 H
Least favorable configuration, 最不利构形
. ^+ O1 _+ D0 G* OLeast favorable distribution, 最不利分布( T* m! y! o: p. B$ N( F
Least significant difference, 最小显著差法" Z. C) Y' k) Q
Least square method, 最小二乘法
! h+ a4 f2 Q( d7 pLeast-absolute-residuals estimates, 最小绝对残差估计# q8 `, G0 x+ x. o# A6 M+ p& a& t
Least-absolute-residuals fit, 最小绝对残差拟合1 {$ ]. e0 o! A" |4 U% f* ^
Least-absolute-residuals line, 最小绝对残差线; S; s8 e" \9 d5 C/ y/ E+ f
Legend, 图例
: z: s5 l9 H* X% h$ W6 gL-estimator, L估计量
, y d. A7 [/ `8 o: c8 V3 h6 J7 V6 pL-estimator of location, 位置L估计量
2 F5 Z; @; ^" F* `; U! k; A+ NL-estimator of scale, 尺度L估计量
; U7 j6 |8 F' Z: j* A) ^+ V7 oLevel, 水平* k# Y) |9 v5 Y
Life expectance, 预期期望寿命/ Z& l. `, r# e- q- ?1 T' `6 F% Y
Life table, 寿命表 ^5 }$ W% O& c. O$ b
Life table method, 生命表法- [3 B. X2 Y2 j @
Light-tailed distribution, 轻尾分布/ m. b( j( O# u$ s3 Q
Likelihood function, 似然函数
* @6 ^9 n7 L* \Likelihood ratio, 似然比# L+ b8 [' y g g
line graph, 线图
* n2 b' S' W: M* |, ^Linear correlation, 直线相关0 e' |* _0 f/ a1 E5 q
Linear equation, 线性方程
( |0 l' h3 m& s- k, B. D4 `Linear programming, 线性规划/ w6 o+ z4 l9 _6 r ]2 `: v( a
Linear regression, 直线回归
" d5 ^. ]) V$ g9 G; f, ]Linear Regression, 线性回归
# E/ R& \3 k) R8 R- ^7 rLinear trend, 线性趋势
1 g6 u4 `6 Y* v+ p8 o& PLoading, 载荷 : T$ q6 [8 v/ z
Location and scale equivariance, 位置尺度同变性, n, H" S% n, G# c
Location equivariance, 位置同变性+ F$ T! m1 l h; [6 {5 N
Location invariance, 位置不变性
# l# v$ M$ G0 U+ V+ W. b2 nLocation scale family, 位置尺度族* j7 ]+ G% _; b+ d! U+ `( k2 ^
Log rank test, 时序检验 ) D1 K" @# G' f- ^/ z. D
Logarithmic curve, 对数曲线/ L* c. q% o& Q$ B! Y# v
Logarithmic normal distribution, 对数正态分布% n( Y) p0 c3 N8 ^7 d9 U( [
Logarithmic scale, 对数尺度& ?5 t: q- N/ v: Y- E: c4 d- T
Logarithmic transformation, 对数变换$ L" G( T0 p) r( |1 ]
Logic check, 逻辑检查
# H3 W1 ~2 b& U9 RLogistic distribution, 逻辑斯特分布
& f1 n* w6 K, c9 b8 ^. u4 K# Z% \) ELogit transformation, Logit转换7 [( U5 Z$ ~& m
LOGLINEAR, 多维列联表通用模型
7 V( U7 c G8 v/ f8 J9 u; ~: {Lognormal distribution, 对数正态分布
; _9 l. v; x5 ]7 ]Lost function, 损失函数0 j6 b" C7 W% K' [# e% ?4 s9 u
Low correlation, 低度相关) d7 H3 E1 N# M# p1 C3 S( f
Lower limit, 下限
' {1 S4 G1 T9 C9 jLowest-attained variance, 最小可达方差
& A0 T2 Z: d8 I7 L& LLSD, 最小显著差法的简称
7 x" d+ y+ r5 f# l* m1 z- A/ TLurking variable, 潜在变量
1 g# T9 E. K6 e! x t2 AMain effect, 主效应+ t- x6 W" `% A
Major heading, 主辞标目
2 }% R5 L* q8 g8 [Marginal density function, 边缘密度函数
0 E: C/ v U5 O' Z, t- X. TMarginal probability, 边缘概率1 m! a" Q6 i5 ~5 d
Marginal probability distribution, 边缘概率分布
0 J2 ~# q( ]. P& F2 @+ SMatched data, 配对资料8 H0 m9 [* k, I' X0 X
Matched distribution, 匹配过分布) K& Y& ?8 K7 _* E$ l& F
Matching of distribution, 分布的匹配
2 c" d9 r* t; s5 q+ N, sMatching of transformation, 变换的匹配& C) v' }; z% D8 l
Mathematical expectation, 数学期望9 A7 W! ]! M" H: V0 ~" Y. d
Mathematical model, 数学模型
- M5 |& n! ^' \Maximum L-estimator, 极大极小L 估计量! K$ k& S4 W; {; t3 G
Maximum likelihood method, 最大似然法# M+ @8 [5 r0 p! R
Mean, 均数: K8 }4 z0 }! v- ?0 e; q: ^' c/ R
Mean squares between groups, 组间均方3 ~, A# W. { |( C4 V
Mean squares within group, 组内均方
7 A. ~& O6 i7 N' a1 I. {Means (Compare means), 均值-均值比较
/ M9 L: Y1 G( r* r% dMedian, 中位数6 H7 v4 M+ u& E
Median effective dose, 半数效量9 K o' R* y# d+ o8 ?" k( {7 E7 }
Median lethal dose, 半数致死量1 s1 n! y( @: E) ]! S" A- ]
Median polish, 中位数平滑
" s0 @ {) Q( o B5 aMedian test, 中位数检验
! k; K5 R, W( @$ C3 XMinimal sufficient statistic, 最小充分统计量% W% C- w) n% S5 n' s# B
Minimum distance estimation, 最小距离估计# z% ~8 I0 Q5 Q$ N
Minimum effective dose, 最小有效量
: x; ]- L2 V0 oMinimum lethal dose, 最小致死量
# Q% t! n8 M: [9 w) ?% HMinimum variance estimator, 最小方差估计量' `3 a! A* ?5 X0 {( A# w
MINITAB, 统计软件包& t R. d& O# H2 ?/ F3 x' a" U
Minor heading, 宾词标目
* [* O/ ]! _* Q) Y2 A2 |3 GMissing data, 缺失值
& N6 J- v( E5 f' D, i" mModel specification, 模型的确定
1 w- k3 b' E) h3 e3 N' e; OModeling Statistics , 模型统计4 H0 R9 Q5 V2 O) A7 D. ~* x8 E
Models for outliers, 离群值模型) k# S' U$ x9 E# v0 d
Modifying the model, 模型的修正. f p$ K3 O; U+ R
Modulus of continuity, 连续性模+ ^8 j! Q9 f& a$ U: Y% O& _& y
Morbidity, 发病率 & w* h! y2 A( V, K; F
Most favorable configuration, 最有利构形; e. M8 N, o! x. t) T* d% s
Multidimensional Scaling (ASCAL), 多维尺度/多维标度5 x6 j8 G. {0 v8 v( O" W
Multinomial Logistic Regression , 多项逻辑斯蒂回归
( v; Y" i; J4 i* f _Multiple comparison, 多重比较
0 x3 t5 W& H' ?% ` |Multiple correlation , 复相关
8 [( z; b j+ s+ k, z0 \Multiple covariance, 多元协方差
) h/ @. }5 R, aMultiple linear regression, 多元线性回归* z# d- k& u/ a+ A- J' t
Multiple response , 多重选项
6 J) K# q4 {6 I( ^Multiple solutions, 多解2 O+ {- O! u; ]. S9 ?# W, A
Multiplication theorem, 乘法定理
! u5 V; x& X+ H/ C& W8 V+ nMultiresponse, 多元响应' ^7 [3 F0 T+ l) @( n/ A6 l
Multi-stage sampling, 多阶段抽样6 X' X+ d |. B: G5 U: t
Multivariate T distribution, 多元T分布
8 @) M7 f: I" L' I. B, B2 aMutual exclusive, 互不相容" y: y, {0 k! K% D! R$ e
Mutual independence, 互相独立. s( l! U3 }+ I& E( }
Natural boundary, 自然边界
6 `" M `$ s7 i- `7 ?2 hNatural dead, 自然死亡
. O& v/ D/ T( L- `" b! pNatural zero, 自然零
, \6 H& r4 L0 j% aNegative correlation, 负相关4 o& \; u% J6 R$ P p7 g0 P" z
Negative linear correlation, 负线性相关
6 ]' B8 Y% d, H* `. sNegatively skewed, 负偏
) r J. I% K1 J+ M+ INewman-Keuls method, q检验$ \4 w0 t3 @5 ^; ?1 f
NK method, q检验
' Y- ~5 b9 U5 F5 j8 C% j- T' ~$ B2 vNo statistical significance, 无统计意义
4 D- ~. w9 S6 F! S5 M3 E4 L9 @8 wNominal variable, 名义变量) C( \- c4 \. k+ d+ R0 F7 S# B
Nonconstancy of variability, 变异的非定常性7 X/ k G# G$ ^) R
Nonlinear regression, 非线性相关$ d, l8 y4 R# ^6 n: M9 P G
Nonparametric statistics, 非参数统计% @, o K/ l: Y0 r2 c2 y; ^; i6 P
Nonparametric test, 非参数检验" O2 n( F$ L) O5 W
Nonparametric tests, 非参数检验
" a4 I. I7 H4 l* y* p( sNormal deviate, 正态离差
2 U4 p1 r' o9 |4 ENormal distribution, 正态分布3 M. I/ X6 g- W8 H) [8 \ Y, {$ @
Normal equation, 正规方程组" x* \& ^+ d* g) C
Normal ranges, 正常范围% \5 `8 x4 V% d0 ]. s
Normal value, 正常值% _4 V: F, Z8 X+ ^% Z
Nuisance parameter, 多余参数/讨厌参数/ _1 Q8 f9 \: t3 U2 v
Null hypothesis, 无效假设 4 R# z$ w+ }8 F, h$ L- Z. M
Numerical variable, 数值变量4 R& d4 m/ h' L/ N$ {# Y
Objective function, 目标函数
! C1 q9 W; T- k \5 h( JObservation unit, 观察单位9 o1 r- y p5 d9 p- Y) g
Observed value, 观察值
: E' d8 N. l3 p- hOne sided test, 单侧检验4 s8 u# z; X9 n
One-way analysis of variance, 单因素方差分析8 X0 `7 Q$ j5 {1 n: J- O. F8 A
Oneway ANOVA , 单因素方差分析8 e/ r* R0 o# f# q ^& X
Open sequential trial, 开放型序贯设计. m, P; N& S8 x6 R
Optrim, 优切尾
. M2 G! K* I! G. L' ?/ oOptrim efficiency, 优切尾效率' @8 D5 x0 D- T# Z) g9 A) {
Order statistics, 顺序统计量
2 S4 C, q, U+ C$ `: YOrdered categories, 有序分类% U8 u C) _( [4 D" N
Ordinal logistic regression , 序数逻辑斯蒂回归5 w3 `4 b# J1 B( ~
Ordinal variable, 有序变量) a0 x, m0 @! q$ p1 s5 u
Orthogonal basis, 正交基# u; d' }' N7 b- _& g
Orthogonal design, 正交试验设计
) J; o) ~9 L; s4 FOrthogonality conditions, 正交条件: A. @! ] C. x2 H( V' }
ORTHOPLAN, 正交设计
% a" _7 E3 G2 L1 I9 QOutlier cutoffs, 离群值截断点
" t3 w7 _; m3 F8 AOutliers, 极端值
$ M5 t# I7 Q1 e) B9 LOVERALS , 多组变量的非线性正规相关
' H2 p: |! @$ vOvershoot, 迭代过度
5 d; e$ D% c3 z1 ^3 LPaired design, 配对设计5 N0 I. b' U$ [3 a7 `; D
Paired sample, 配对样本
# E. z& m5 o. l' T+ fPairwise slopes, 成对斜率
$ V# Q3 |( S* O# w) A" d4 iParabola, 抛物线
( z$ @, t: k7 g1 KParallel tests, 平行试验
% F0 V0 o+ o' B/ H1 q# {Parameter, 参数+ `8 U [8 D0 `' i! n
Parametric statistics, 参数统计1 I- A+ Y/ a8 y4 j% q/ ^2 g* a
Parametric test, 参数检验$ S/ E) ~" r& q
Partial correlation, 偏相关
5 T6 I" m; b% h/ I, sPartial regression, 偏回归
+ a, T/ c, _ W1 x4 tPartial sorting, 偏排序
+ v. w! ]8 H7 u4 Z9 hPartials residuals, 偏残差
, g6 J* R7 B5 W* e3 K8 y1 JPattern, 模式
: r) W, [! V% K* U. ?, iPearson curves, 皮尔逊曲线
6 O' R/ ~3 }( Z9 @0 c, H* _. P! tPeeling, 退层
& V9 Q, N; X' _3 \: v) B7 pPercent bar graph, 百分条形图
: }+ Y* i' @6 A+ n/ ~Percentage, 百分比! N+ k! ]2 ]( f7 n& h" {+ U
Percentile, 百分位数0 e) h6 [7 _9 E8 {; ]5 |" V
Percentile curves, 百分位曲线- E8 ~" g4 k% |* {
Periodicity, 周期性" r1 q4 H- ] r. X: Z1 {8 e! m
Permutation, 排列$ i% c' Y }& _4 g* X; B
P-estimator, P估计量1 m& C: Z: E* A* ^ I) H6 J* Y' f
Pie graph, 饼图 U% n; x3 m& \! _' ^; n
Pitman estimator, 皮特曼估计量
`4 _& @, j' ]" hPivot, 枢轴量
" `) ]6 @. S1 \Planar, 平坦; Z2 X+ Q- A! d2 b( w9 A$ q2 b
Planar assumption, 平面的假设
# O) n/ b$ h/ I2 w' PPLANCARDS, 生成试验的计划卡
/ }/ ~- c3 L% V7 a. ZPoint estimation, 点估计
5 u) f5 }* I. i! L" s4 p+ kPoisson distribution, 泊松分布! h1 T! S5 L5 v$ [# a4 ~0 P$ p
Polishing, 平滑
3 `7 L+ Q/ u" Z" F4 `4 G9 ~Polled standard deviation, 合并标准差
- B# R) |$ K: |* G# j* R) M+ d% LPolled variance, 合并方差8 D0 U2 B- M8 c4 N6 c. q1 W/ o6 C
Polygon, 多边图
3 J. S' U# ~+ q4 w7 rPolynomial, 多项式+ Q+ R4 [( ?2 @, J5 z2 K
Polynomial curve, 多项式曲线( j3 I6 @$ F9 t5 H4 _" B D% n
Population, 总体
K m4 p+ b- B2 |6 K- a$ [Population attributable risk, 人群归因危险度/ h% ~: I1 }7 S
Positive correlation, 正相关
( _& N. L. j( ?Positively skewed, 正偏; }( X4 o, W$ k D! D+ {, M
Posterior distribution, 后验分布$ ?( f1 {$ c1 {1 Q
Power of a test, 检验效能8 U' Y: T% ?, E; z7 X8 s
Precision, 精密度, A, K6 }, J& K) P# B) O+ c, M
Predicted value, 预测值
# m# ^( z8 R x2 j0 O% k: cPreliminary analysis, 预备性分析
& B1 t: `/ k% ^$ X' M3 [; h8 k3 a L# U5 bPrincipal component analysis, 主成分分析
6 u# N' j4 z5 a3 J, RPrior distribution, 先验分布4 u; [: ~- r1 O8 w; V; c
Prior probability, 先验概率
5 j) C; j2 ]- Y ~ t CProbabilistic model, 概率模型' {0 J; Q9 n9 u5 i# ^
probability, 概率
$ S0 \5 t% t7 o4 K2 IProbability density, 概率密度. l5 k C+ C1 U" R* S: N
Product moment, 乘积矩/协方差
5 B2 n2 e8 F) F- Y: R# P; q6 vProfile trace, 截面迹图3 H3 r1 b0 ]0 R/ x8 q
Proportion, 比/构成比% Z$ X# w3 g4 S
Proportion allocation in stratified random sampling, 按比例分层随机抽样- c; a* G3 P+ i# J& W4 g* H
Proportionate, 成比例
- D/ w* B9 L( a( C, w. T0 D( A8 U' KProportionate sub-class numbers, 成比例次级组含量6 x% Q' y; Y) p& G, y
Prospective study, 前瞻性调查6 _9 `; P6 {5 _7 f, T
Proximities, 亲近性 5 @* Z# {+ V1 Z
Pseudo F test, 近似F检验
) c2 ~! b/ e% Z% C, q" p3 DPseudo model, 近似模型
, o( B" b) \/ TPseudosigma, 伪标准差$ G9 d/ A- B, m D% Q& ]! }0 d
Purposive sampling, 有目的抽样
9 v' }" i- N5 f9 B* EQR decomposition, QR分解1 I! Q, A. y7 J. S
Quadratic approximation, 二次近似
4 [* k, Z4 v" f) W" \Qualitative classification, 属性分类( i K( D5 e& G+ j. o) v
Qualitative method, 定性方法
# c8 w+ v8 H9 AQuantile-quantile plot, 分位数-分位数图/Q-Q图) I% s2 p/ G7 H* W3 v1 c7 P E$ r: j
Quantitative analysis, 定量分析. l" F% ^/ m6 X2 {6 ~
Quartile, 四分位数3 S) J; d- t$ P5 O5 k! C+ p) A2 q
Quick Cluster, 快速聚类
8 Q% [" u& R$ X u- aRadix sort, 基数排序! }' Z6 ?7 b: G
Random allocation, 随机化分组. L, K0 {8 g, g$ M1 t8 P
Random blocks design, 随机区组设计
4 k0 ^; N( _! q- x& U) ~, }Random event, 随机事件
\1 e+ h* c( K2 }+ K5 c) nRandomization, 随机化
: A. C4 H. @+ o/ S" _- r+ H4 bRange, 极差/全距
/ P- h- _7 h4 b2 q1 p# [4 iRank correlation, 等级相关
% b( n1 U+ l+ ERank sum test, 秩和检验2 Y* M$ [6 ~5 I; H. c8 r: q6 d
Rank test, 秩检验
" n& ^* a8 C; m9 H) I' J/ R6 iRanked data, 等级资料
" Q- o4 V6 m5 W- Q& v3 CRate, 比率: g( N, a ^" f% {' ~
Ratio, 比例0 D, r3 e( C( X q/ x3 i
Raw data, 原始资料/ u, D! P/ m Z0 E( l( y! x0 o9 R
Raw residual, 原始残差
8 J2 Y; Y$ V. Q% L; ]Rayleigh's test, 雷氏检验6 o2 _& H. w3 _6 ?2 c
Rayleigh's Z, 雷氏Z值
1 O' d8 t# c) T3 \% [Reciprocal, 倒数
. x2 s! O; A, j( PReciprocal transformation, 倒数变换
- H+ a2 m* s2 _" }& K% {Recording, 记录 v" L* V. A% B5 E3 w) ?
Redescending estimators, 回降估计量/ U+ C2 G- y4 @7 H% Q8 w
Reducing dimensions, 降维3 J( j2 b; n! r: s
Re-expression, 重新表达' B- `9 ~ n0 L
Reference set, 标准组3 k, v, `/ g, j- L2 `1 S7 l
Region of acceptance, 接受域$ Z' }+ N& T4 f# b C: p8 X
Regression coefficient, 回归系数) I3 b6 d9 H& r% ]
Regression sum of square, 回归平方和
" Y- `9 Z" }" zRejection point, 拒绝点
7 f) j" g0 [% V8 qRelative dispersion, 相对离散度: [. z/ `5 _. f# j8 Z
Relative number, 相对数
1 ?; g7 Q, T ~3 C5 {' UReliability, 可靠性
5 M0 E9 p0 l/ |; Q- x& V. ?+ a4 e, b @' `Reparametrization, 重新设置参数
! g- `4 [3 f e* B. OReplication, 重复
' b3 @- h" I7 p" I, l* wReport Summaries, 报告摘要
" _, d: S+ Z3 f; tResidual sum of square, 剩余平方和
S7 }8 k+ V U! _Resistance, 耐抗性" Q) t, x( C( m. r' D+ a
Resistant line, 耐抗线
- P# o" j8 |+ I( q2 v1 o ?$ ]: ?Resistant technique, 耐抗技术
w8 J+ F) J# J$ Z8 KR-estimator of location, 位置R估计量/ T: [! T6 C4 K: y1 N- _, F) g
R-estimator of scale, 尺度R估计量
S8 k7 E% W, t3 a+ Q; H! h$ kRetrospective study, 回顾性调查: F, M& `0 ]' z
Ridge trace, 岭迹+ }" U. `# L" q" T1 N% p
Ridit analysis, Ridit分析8 `6 D4 Q" v) ^8 _: x# M
Rotation, 旋转0 e( H9 N4 b. U' Z. W0 ^
Rounding, 舍入- x# B Z% I6 n
Row, 行) e6 A7 K9 a% c P1 X0 ?- ?+ H
Row effects, 行效应
7 R, G# n9 ?2 P6 u9 T8 a+ C3 B8 HRow factor, 行因素) s4 F. g3 I% Z* H" V
RXC table, RXC表
% U. X( ?! c+ z- j5 z) U, R4 V' ~Sample, 样本
* y5 g0 o7 L* w/ m* bSample regression coefficient, 样本回归系数; f) Q6 d3 U/ {! B6 b
Sample size, 样本量
3 D6 w* W+ a; I( m- Q3 @' u XSample standard deviation, 样本标准差
& q: K) q M. `, ZSampling error, 抽样误差
9 S- |& `) V, s5 s6 ~( f$ r# ]6 X2 ~SAS(Statistical analysis system ), SAS统计软件包7 n z" T: \0 o w+ W
Scale, 尺度/量表7 v' W5 b% d4 d+ X5 K/ b4 [
Scatter diagram, 散点图3 Z+ G; f5 N% ~; V; R
Schematic plot, 示意图/简图
7 z. Z+ E j& V, k d$ a4 o+ iScore test, 计分检验
$ U$ X* R; M3 I: ]( VScreening, 筛检
+ C- B& O9 T3 v" z/ nSEASON, 季节分析 % L& W* p# b+ a1 _ ^# ^
Second derivative, 二阶导数
; ^3 s \# G9 E& G5 Z' U+ S0 iSecond principal component, 第二主成分
% a+ T+ W& y% q9 X4 p. n4 m! b+ ]; `SEM (Structural equation modeling), 结构化方程模型
4 n7 t! b( ~! R m' Z2 ^; O$ Z NSemi-logarithmic graph, 半对数图
5 ~ y) q; w1 b j. w& Q. DSemi-logarithmic paper, 半对数格纸7 f8 V6 e; K8 @5 I
Sensitivity curve, 敏感度曲线
" P9 X& ]! U, b4 g! J USequential analysis, 贯序分析6 {( ?1 B. V* `5 S! k& R
Sequential data set, 顺序数据集
, U1 v/ V7 K3 {8 H \2 X8 \Sequential design, 贯序设计1 L$ v( A; N& X. z6 A( M
Sequential method, 贯序法
) T& K1 F1 }$ @! t# zSequential test, 贯序检验法9 m% ?3 [+ p2 @9 a, Y
Serial tests, 系列试验) d% |3 ?. b" o3 n
Short-cut method, 简捷法
" W1 |0 _: y. d* M( p% iSigmoid curve, S形曲线- h! B+ Z/ Y+ p( M/ M
Sign function, 正负号函数
2 f) t: N' }7 \ }4 ISign test, 符号检验; G9 c9 J& |' g. |; p
Signed rank, 符号秩
- Y5 g3 [1 L* o# QSignificance test, 显著性检验
! E: L( Y+ c# \4 d$ D' RSignificant figure, 有效数字. s8 E1 a* b7 n; @
Simple cluster sampling, 简单整群抽样
' |. P: U# p& u' H: |Simple correlation, 简单相关
9 B# Y3 k# J2 a; A; \Simple random sampling, 简单随机抽样) g+ N. |9 F( q0 W( \
Simple regression, 简单回归( h* r- ?) Y+ p9 J
simple table, 简单表
5 l. i; T5 }" A# U1 i7 DSine estimator, 正弦估计量% B; {1 P ^! |# j
Single-valued estimate, 单值估计# O5 W1 o- i) @0 ?9 d, c
Singular matrix, 奇异矩阵
. i; ?" U; `% l l) |Skewed distribution, 偏斜分布
9 F; X' Z: S( ?* c; q! a5 oSkewness, 偏度# H1 q) i; J( B+ Y
Slash distribution, 斜线分布0 m/ e$ d" K, ?( y9 Y8 C" z* @! b
Slope, 斜率2 I1 B; V' h; H D3 f9 I
Smirnov test, 斯米尔诺夫检验. Q' c, ?" d7 ?$ D& Z
Source of variation, 变异来源/ L. S9 }1 A9 N3 P+ `' P& F% ^
Spearman rank correlation, 斯皮尔曼等级相关
. s) L' s1 {/ A! s( `: HSpecific factor, 特殊因子6 B4 j3 o$ E) P4 Z ?0 Y
Specific factor variance, 特殊因子方差
. b( P. ?* d- _Spectra , 频谱* _6 Y x! O& k( m) c
Spherical distribution, 球型正态分布
; Z/ e y; `4 t6 mSpread, 展布% v% g& j- b4 y
SPSS(Statistical package for the social science), SPSS统计软件包' P) x9 l$ W2 z, n1 f! ~
Spurious correlation, 假性相关& a, N& \ P/ d! L
Square root transformation, 平方根变换% q6 k$ l+ k5 h! F( u
Stabilizing variance, 稳定方差
5 d/ D- M+ n* oStandard deviation, 标准差
, g* r$ t, M: Z6 n5 a. DStandard error, 标准误
/ q7 z2 ]; @9 q& M( t) `Standard error of difference, 差别的标准误
. D# X# S5 h$ _. y6 W& ?Standard error of estimate, 标准估计误差
5 x1 R7 \. a% V0 ?Standard error of rate, 率的标准误
+ W2 `% H1 S9 T& F" PStandard normal distribution, 标准正态分布; w; y: Q( r/ ^
Standardization, 标准化
& ~: {' Y7 H# [$ ~6 C9 [( QStarting value, 起始值
- c& S: ^# Z/ l: o/ E8 w+ GStatistic, 统计量( D; T; W, Y4 M/ z/ k
Statistical control, 统计控制 o$ E9 d. A2 i
Statistical graph, 统计图
0 j9 r* D' B' {Statistical inference, 统计推断
( h/ s) `& W- [; E8 u5 S% qStatistical table, 统计表1 w K- N& F2 ^4 H6 ^" L
Steepest descent, 最速下降法
- o) q4 _4 s* H5 g( m) OStem and leaf display, 茎叶图
5 z1 H& V8 i- x& r$ I4 G! H1 v3 UStep factor, 步长因子/ R3 C, o: T# F+ b2 P: ?* p
Stepwise regression, 逐步回归
3 j, p. a7 J4 xStorage, 存( G1 a, o3 I! q* ~2 B Z/ t
Strata, 层（复数）4 S; w2 {+ x: c& J
Stratified sampling, 分层抽样( b6 O5 J) z, A6 F
Stratified sampling, 分层抽样
: E$ l: f$ I0 zStrength, 强度
. J7 ^2 w1 t7 L- A* aStringency, 严密性
8 o; _1 ` ^0 C& {7 kStructural relationship, 结构关系! R& m4 q0 e+ j; B; J( @4 N
Studentized residual, 学生化残差/t化残差5 `/ T5 z; h6 U7 A6 @
Sub-class numbers, 次级组含量
2 ~, Y7 ~- o+ c0 `8 X/ ZSubdividing, 分割# U: a# e1 R. N# E/ U- w
Sufficient statistic, 充分统计量
0 H& w4 V( \1 G* _8 p( OSum of products, 积和
& A: _5 H' f0 Z; s/ y* vSum of squares, 离差平方和' Y9 z& |% n2 [: T
Sum of squares about regression, 回归平方和) @' W" c, Y; L
Sum of squares between groups, 组间平方和) o" I0 r3 c# A5 A+ a% @
Sum of squares of partial regression, 偏回归平方和8 I7 {- m9 M* `2 Y, b7 p
Sure event, 必然事件7 r7 H, I; }( V! P% i
Survey, 调查
+ Z% I" e2 g0 z0 H) {6 j2 N; B' ESurvival, 生存分析6 s$ q {" r. o# C) G, P
Survival rate, 生存率; h4 `7 N9 ~% c6 d( A9 e1 V& S/ d
Suspended root gram, 悬吊根图
' y9 p* T% }% k8 Q: j: x) eSymmetry, 对称
$ K- ^' m+ `. y0 f fSystematic error, 系统误差
}6 _2 ]0 a) ZSystematic sampling, 系统抽样6 E+ P: j% E0 `
Tags, 标签4 Z% q t5 D1 d+ @$ U1 G! w
Tail area, 尾部面积
/ o8 W" [) M" e: e% Y3 |% oTail length, 尾长& d9 t3 I; p9 |) j
Tail weight, 尾重
5 o1 q% e3 F2 `5 }. qTangent line, 切线0 K# q- j6 Y* |# u
Target distribution, 目标分布
, H( B1 f# o9 B, i; J3 FTaylor series, 泰勒级数
* b( [7 h5 D3 t& C. gTendency of dispersion, 离散趋势
) ?$ b$ O3 I+ U G) zTesting of hypotheses, 假设检验
( ^4 N1 k7 R& d! BTheoretical frequency, 理论频数2 G7 x. R! R2 V. }+ P7 ~
Time series, 时间序列) z* i: _/ g* R! ~0 m: [5 `$ }3 Y9 ?
Tolerance interval, 容忍区间4 B: H$ s& w; f7 ]
Tolerance lower limit, 容忍下限
8 y. a. y: ?9 S7 M6 @4 X; K7 \Tolerance upper limit, 容忍上限
0 Z$ z4 \0 M3 A4 V, |$ @Torsion, 扰率% j ]% w) k4 l2 y: u' l$ F# {
Total sum of square, 总平方和5 @0 G# E" o6 _# }9 f/ y
Total variation, 总变异
7 O' {& f' Z' [$ \, s: m; eTransformation, 转换$ G6 v6 g* M y$ K5 Y4 |
Treatment, 处理4 q0 W/ F. E2 ?, A; Q" m
Trend, 趋势
# T& k( r% O3 N, J) ?/ L# R* OTrend of percentage, 百分比趋势
7 Y* S- h+ [9 l6 nTrial, 试验, M* u- O$ J9 M1 K
Trial and error method, 试错法6 D6 I6 N' j+ Q- m1 C: v" r* ~
Tuning constant, 细调常数
3 F* e, t4 q$ q3 c: }9 W( N% n) BTwo sided test, 双向检验
V- Q: C" ^; _' ATwo-stage least squares, 二阶最小平方
3 H# h- ?* d$ J4 A# g6 |Two-stage sampling, 二阶段抽样
: n: J$ Y g* R( w8 ]! UTwo-tailed test, 双侧检验
4 [1 X- h/ x4 PTwo-way analysis of variance, 双因素方差分析
2 P Y! i) R+ w/ t2 q3 FTwo-way table, 双向表9 w& P& k0 Z) N3 S9 H: u7 ]
Type I error, 一类错误/α错误6 t( L2 _7 E# S& K& C+ |8 T
Type II error, 二类错误/β错误- T5 P* g3 w! S- X+ G6 n
UMVU, 方差一致最小无偏估计简称+ O7 K6 j! _/ K3 i" W5 _
Unbiased estimate, 无偏估计
' s7 d" |$ O9 fUnconstrained nonlinear regression , 无约束非线性回归
2 Z4 L! @9 q# s- J) o/ G5 ~1 XUnequal subclass number, 不等次级组含量
5 c2 v* x, G9 y5 p' OUngrouped data, 不分组资料
: b3 V' [' w+ F0 s4 I! dUniform coordinate, 均匀坐标* e2 F4 S% y6 ]6 T" |5 U
Uniform distribution, 均匀分布
/ |1 K$ S9 D0 K4 K; g/ b2 ^Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
- v* `! e! y1 s, m" eUnit, 单元9 A) I( j7 A7 y1 A
Unordered categories, 无序分类
" L: v" L" \9 n; o6 k; BUpper limit, 上限
* F2 I% E7 L5 |* M$ I! bUpward rank, 升秩# k1 @7 `0 j$ P+ W. c, u
Vague concept, 模糊概念; j) B, d) \; H6 Q9 C
Validity, 有效性
0 m( c/ L- Z$ F2 eVARCOMP (Variance component estimation), 方差元素估计% a) _3 k- L: e1 L
Variability, 变异性
0 l" D. l% I- b% s$ ~& F2 {6 K; h+ K1 _4 vVariable, 变量+ L3 B4 C* p, C' s
Variance, 方差3 k8 W T6 O# K* M& h
Variation, 变异
9 I* k1 \$ [! D O. I" HVarimax orthogonal rotation, 方差最大正交旋转
9 p* I4 Y8 V, rVolume of distribution, 容积
- y, t4 N6 W& J# rW test, W检验' U! B8 r. C2 ?* u1 d- p
Weibull distribution, 威布尔分布! q2 n8 _8 `+ y" O8 i1 K- [% c
Weight, 权数9 l6 l; t( |+ K( M. Q
Weighted Chi-square test, 加权卡方检验/Cochran检验
# N8 }- z1 ~% s8 R% g- m5 sWeighted linear regression method, 加权直线回归( P u* R7 n2 K, e% U9 K
Weighted mean, 加权平均数
5 m; i; C; @" i; P' {Weighted mean square, 加权平均方差
( u+ V. G) Q3 bWeighted sum of square, 加权平方和
8 k; G( P% `1 d) SWeighting coefficient, 权重系数
: V. G9 I% b! a" {# a$ r8 UWeighting method, 加权法
" l& `8 Y: Y% bW-estimation, W估计量
& V( j4 I. B5 c6 zW-estimation of location, 位置W估计量
0 ^- d7 c; H* ~9 S0 |- I: |" i- O8 P( sWidth, 宽度3 K1 M* Y( \5 Y
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
, X5 v: W8 S5 t8 F! pWild point, 野点/狂点3 U- w- T# l/ m
Wild value, 野值/狂值3 L6 p3 n* H3 B) q6 i9 C
Winsorized mean, 缩尾均值
" z! G0 p1 p# T8 b6 ?+ vWithdraw, 失访
) z& s( q0 H) h0 `Youden's index, 尤登指数
" t% E8 P0 Q& U" C/ H( DZ test, Z检验' @" \9 `2 k% Q
Zero correlation, 零相关
) a+ A& l6 {) a" X- n1 QZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
